| # ICBINP ONNX Laria Bundle | |
| ONNX image-generation bundle prepared for Laria Android/Python parity testing. | |
| ## Layout | |
| - `tokenizer/` | |
| - `scheduler/scheduler_config.json` | |
| - `text_encoder/model.onnx` | |
| - `unet/model.onnx` | |
| - `unet/model.onnx.data` | |
| - `vae_encoder/model.onnx` | |
| - `vae_encoder/config.json` | |
| - `vae_decoder/model.onnx` | |
| ## Notes | |
| - This model behaves like a classic Stable Diffusion pipeline and requires | |
| classifier-free guidance for coherent output. | |
| - Python validation used guidance scale `5.0`. | |
| - Img2img requires the included `vae_encoder`. | |
| - The `vae_encoder/config.json` only carries the VAE scaling factor needed by | |
| the local pipeline. | |
| ## Local Test Scripts | |
| Reference scripts live in the companion ONNX bench: | |
| - `onnx_txt2img_ICBINP.py` | |
| - `onnx_img2img_ICBINP.py` | |